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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

The Data Scientist profession today is often considered to be one of the most promising and lucrative. The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Previously, such problems were dealt with by specialists in mathematics and statistics.

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How Gilead used Amazon Redshift to quickly and cost-effectively load third-party medical claims data

AWS Big Data

Because Gilead is expanding into biologics and large molecule therapies, and has an ambitious goal of launching 10 innovative therapies by 2030, there is heavy emphasis on using data with AI and machine learning (ML) to accelerate the drug discovery pipeline. This data volume is expected to increase monthly and is fully refreshed each month.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. You can get faster insights without spending valuable time managing your data warehouse.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” First, data isn’t created in a uniform, consistent format.

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The value of CDP Public Cloud over legacy Hadoop-on-IaaS implementations

Cloudera

The intent of this article is to articulate and quantify the value proposition of CDP Public Cloud versus legacy IaaS deployments and illustrate why Cloudera technology is the ideal cloud platform to migrate big data workloads off of IaaS deployments. data streaming, data engineering, data warehousing etc.),